No abstract

Extracting of car license plate is important for identifying the car. Since there are some problems such as poor ambient lighting problem , bad weather problem and so on , the car images are distorted and the car license plate is difficult to be extracted. This paper proposes a method of extracting car license plate using motor vehicle regulation. In this method , some features of car license plate according to motor vehicle regulation such as color information , shape are applied to determine the candidates of car license plates. To certify the license plate , the characters , numbers and their patterns are recognized by backpropagation neural networks in windows which are opened in those boundaries of candidates. For the results of recognition by neural networks , the candidate which has characters and numbers patterns according to motor vehicle regulation is certified as license-plate region. Since the results of characters-pattern recognition is used to certify the license plate , the ability of license-plate extracting is enhanced and the car is identified simultaneously. The results of the experiments with 70 samples of real car images show the performance of car license-plate extraction by 84.29% , and the recognition rate is 80.81%.